Methods and systems for speech signal processing

ABSTRACT

Methods and systems for speech signal processing an interactive speech are described. Digitized audio data comprising a user query from a user is received over a network in association with a user identifier. A protocol associated with the user identifier is accessed. A personalized interaction model associated with the user identifier is accessed. A response is generated using the personalized interaction model and the protocol. The response is audibly reproduced by a voice assistance device.

INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS

Any and all applications for which a foreign or domestic priority claimis identified in the Application Data Sheet as filed with the presentapplication are hereby incorporated by reference under 37 CFR 1.57.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentand/or the patent disclosure as it appears in the United States Patentand Trademark Office patent file and/or records, but otherwise reservesall copyrights whatsoever.

BACKGROUND OF THE INVENTION Field of the Invention

The present disclosure generally relates to speech signal processing andmore specifically to an interactive speech system.

Description of the Related Art

Conventional interactive speech systems fail to provide adequatepersonalization and fail to provide adequate interactivity with respectto user-specific medical care instructions.

SUMMARY

The following presents a simplified summary of one or more aspects inorder to provide a basic understanding of such aspects. This summary isnot an extensive overview of all contemplated aspects, and is intendedto neither identify key or critical elements of all aspects nordelineate the scope of any or all aspects. Its sole purpose is topresent some concepts of one or more aspects in a simplified form as aprelude to the more detailed description that is presented later.

An aspect of the present disclosure relates to a system, comprising: anetwork interface; at least one processing device operable to: receivedigitized audio data comprising a user query from a user; receive a useridentifier associated with the digitized audio data; access apersonalized interaction model corresponding to the user identifier;access a first protocol associated with the user identifier; utilize thepersonalized interaction model and the first protocol to generate aresponse; and cause the response to be audibly reproduced by a userdevice.

An aspect of the present disclosure relates to a system, comprising: anetwork interface; at least one processing device operable to: receiveover a network using the network interface digitized audio datacomprising a user query from a user, the digitized audio data streamedin real time from a user device; receive over the network using thenetwork interface a user identifier associated with the digitized audiodata; use a natural language processing engine to: translate thedigitized audio data to text; identify, from the translated digitizedaudio data, a user intent associated with the query; identify, from thetranslated digitized audio data, a variable associated with the userintent; identify, using the user intent identified using the naturallanguage processing engine, what computerized service to invoke; accessfrom computer readable memory a personalized interaction modelcorresponding to the user identifier; access from computer readablememory a first protocol associated with the user identifier; access,using a computer resource, a current date and time; parse the firstprotocol to identify a first activity identified in the first protocol,the first activity identified in the first protocol associated with aspecified date range and/or time period, that corresponds to the currentdate and/or time; utilize: the personalized interaction model, the firstprotocol, the identified first activity, the variable associated withthe user intent, and the computerized service identified using the userintent, to generate a response to the user query; and cause the responseto the user query to be transmitted to and audibly reproduced by theuser device.

An aspect of the present disclosure relates to a computerized method,the method comprising: receiving over a network using a networkinterface digitized audio data comprising a user communication from auser, the digitized audio data received in real time from a user device;receiving over the network using the network interface data identifyingthe user; using a natural language processing engine to: translate thedigitized audio data to text; identify a user intent associated with thecommunication; identify a variable associated with the user intent;identifying, using the user intent identified using the natural languageprocessing engine, what computerized service to invoke; accessing apersonalized interaction model corresponding to the data identifying theuser; accessing from computer readable memory a first protocolassociated with the user; parsing the first protocol to identify a firstrule identified in the first protocol; utilizing: the personalizedinteraction model, the first protocol, the identified first activity,the variable associated with the user intent, and the computerizedservice identified using the user intent, to generate a response to theuser communication; and causing the response to the user communicationto be transmitted to and audibly reproduced by the user device.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments will now be described with reference to the drawingssummarized below. These drawings and the associated description areprovided to illustrate example aspects of the disclosure, and not tolimit the scope of the invention.

FIG. 1 illustrates an example multi-system architecture.

FIG. 2 illustrates an example voice assistant device architecture.

FIG. 3 illustrates an example voice interaction system.

FIG. 4 illustrates an example personalized model generation process.

FIG. 5 illustrates an example voice session process.

FIG. 6 illustrates an example response generation process.

FIG. 7 illustrates an example natural language analysis of a protocoldocument.

FIG. 8 illustrates an example conflict detection process.

FIGS. 9-12 illustrate an example voice interaction system architectureand related processes.

DETAILED DESCRIPTION

An aspect of the present disclosure relates to systems and methods forproviding interactive voice-based and/or text-based sessions withpersonalized user responses, using contextual understanding. An aspectof the present disclosure relates to systems and methods that provideinteractive voice-based and/or text-based sessions with a patientregarding patient care with individualized experiences. An aspect of thepresent disclosure relates to improving interactive voice-based and/ortext-based sessions so that they are more natural, interpret userqueries more accurately, and generate query responses with greateraccuracy. An aspect of the present disclosure relates to systems andmethods that access a static document, such as a patient care/protocoldocument, and utilize such document to provide interactive voice-basedand/or text-based sessions with a patient regarding patient care. Anaspect of the present disclosure relates to providing continuous speechrecognition.

Although the following description generally discusses voice-basedinteractive systems, it is understood that a user may instead interact(using a user device) with the described systems via text, via images (astill image or a video comprising multiple images), or a combination ofvoice, text and/or images. For example, the user may submit queries viatext, and the system may respond using voice (where the voice isreproduced by a user device comprising a speaker). By way of furtherexample, the user may submit queries via voice (e.g., via a user devicemicrophone), and the system may respond using text (which may bedisplayed by a user device display). By way of yet further example, theuser may submit queries via text (e.g., using a user device keyboard),and the system may respond using text (which may be displayed by a userdevice display). Text-based interactions may be particularlyadvantageous where a user has hearing deficits, or where the user livingsituation (e.g., the presence of roommates) makes it difficult to haveprivate interactive voice sessions.

By way of additional example, if a user submits a query (e.g., via voiceor text) regarding a medication (e.g., “what medication am I supposed totake in the morning”), the interactive system may provide a digitizedaudible voice response (e.g., stating the medication name and how muchmedication the user is to take) to the user device for reproduction, andmay access and transmit an image of the medication (e.g., a pill) fordisplay on a user device display, optionally in associated with textproviding instructions regarding the medication dosage. By way of stillfurther example, if a user submits a query (e.g., via voice, text,and/or images (e.g., sign language queries)) regarding an exercise ormedical operation, the interactive system may present provide an audiblevoice response (e.g., providing corresponding instructions), and mayaccess and transmit a video to the user device (e.g., stream the videoor download the video as a file to the user device) visually depictinghow the exercise is to be performed or how the medical device is to beoperated, and the user device may play the video on the user devicedisplay. For example, the video may include a recording of a personperforming the exercise or an animation indicating how the exercise isto be performed.

Typically, when a new medical event (e.g., a new diagnosis, majorsurgery and/or an accident) occurs with respect to a patient, there is asignificant increase in the complexity and/or volume of encounters withmedical service providers, instructions and prescription drugs for thepatient, which may last a significant amount of time.

For example, when a patient visits a doctor or undergoes a medicalintervention (e.g., surgery, chemotherapy, dialysis, debridement, tests(e.g., colonoscopy), etc.), the patient may be provided with a document(sometimes referred to herein as a patient care document or protocoldocument) including preparation instructions prior to the interventionand/or instructions to be followed after the intervention.

By way of illustration, conventionally, when a patient receives a newdiagnosis of a life-changing illness (cancer, major chronic condition)or undergoes surgery with a lengthy rehabilitation period, the patienttypically receives a document including written instructions orprotocols designed to: 1) answer common questions; 2) outlinesignificant care management activities (e.g., preparation for aprocedure, wound care, pain management, physical therapy, medications,etc.); and 3) set expectations regarding when certain activities shouldoccur.

However, such conventional documents and instructions are both staticand generic, requiring the patient and caregiver to interpret whichdetails apply and which ones do not apply to their particular situation.Further, such documents and instructions are often confusing topatients, and yet patients may be embarrassed to ask the physician orother medical professional to explain the document, even when thepatient may have many questions. For example, the patient (or caretakeror family member) may have questions regarding newly prescribed drugs,such as their purpose, side effects, interactions with otherprescription drugs, non-prescription drugs, alcohol, recreational drugs,food, etc. By way of further example, the patient may have questionsregarding protocols the patient is instructed to follow, such as whathappens when, when are they allowed to perform certain activities (e.g.,bathe, shower, perform certain types of exercise, etc.), and whathappens next. The patient (or caretaker or family member) may also havequestions regarding future encounters with medical service providers andevents, such as when do they occur, what is the encounter (e.g., test orprocedure) for, what can the patient expect, what should the patient door not do in advance of the encounter and when, what happens if thepatient misses an appointment, etc. Patients are often at home when suchquestions occur to them, but are reluctant to ‘bother’ the doctor afterthe visit. Likewise, doctors have little time during the office visit,may overlook what other doctors have prescribed, and often lack theknowledge to address all of these questions in the moment, leaving thepatient rushed and confused. As a result, the chance of an avoidableadverse event increases significantly.

Still further, patients often lose such documents and are embarrassed toask the physician for additional copies. Additionally, patients oftenlose track of how long it has been since they had a given procedure, andhence do not know the types and amounts of medications the patientshould be taking at a given point in time. Yet further, some patientssuffer from short term memory loss, so even if a patient is willing tocall the physician regarding the care plan, the patient may forget thephysician's clarifications and instructions. Still further, if a patientis willing to call the physician regarding the care plan, the patientmay be inefficiently utilizing the physician communication system andmay take the physician from other patients to answer routine questions.

To illustrate the potential complexity of a patient care plan, arelatively simple example will now be provided. The example care planmay be for a type of surgery.

Week 1

-   -   Medication        -   Take 2 (pain relief medication) pills every 4 hours.        -   Take 1 (antibiotic) pill after breakfast.        -   Take 1 (antibiotic) after supper.        -   Ice (body part).    -   Exercises        -   Do 10 repetitions of (exercise #1)        -   Do 5 minutes of (exercise #2) twice a day    -   Follow-up Inspection    -   Visit doctor on Mar. 3, 2018 for inspection of incisions and        removal of stitches.    -   Goals        -   Decrease pain        -   Range of motion <90 degrees (until stitches removed).

Weeks 2-3

-   -   Medication        -   Take 1 (pain relief medication) pills every 4 hours.        -   Ice (body part).    -   Exercises        -   Do 20 repetitions of (exercise #1)        -   Do 10 minutes of (exercise #2) twice a day    -   Goals        -   Decrease pain        -   Range of motion 120 degrees.

Weeks 4-6

-   -   Exercises        -   Do 20 repetitions of (exercise #1)        -   Do 20 minutes of (exercise #2) twice a day        -   Do 15 minutes of (exercise 3 2) twice a day    -   Goals        -   Range of motion 180 degrees.    -   Follow-up Inspection        -   Visit doctor on Apr. 3, 2018 for check-up.

In order to address one or more of the foregoing deficiencies, an aspectof the present disclosure relates to systems and methods tointeractively interact with a patient (and/or other users, such asfamily members and caretakers). Patients are enabled to have clearquestion and answer interactions with the system with respect to theinstructions (e.g., protocols) provided by their medical serviceproviders. This makes the protocols more understandable and usable,which ultimately makes them easier for the patient to correctly follow.

For example, systems and methods are disclosed that are configured torespond to user questions regarding: instructions provided by a medicalservice provider (e.g., a physician, dentist, pharmacist, optometrist,therapist, nurse-practitioner, nurse, etc.); medications; medicalconditions; lab and test results; and the user's medical history. Thus,aspects of the disclosure relate to providing a user-friendly systemthat enable patients to get answers to questions related to theirmedical condition and treatment (e.g., what, how, and why questions) anddo so within the context of their specific medical history, personality,and individual preferences (which may be expressly provided and/orinferred based on patient behavior).

Although certain examples will be described with respect to interactionswith a patient, the example processes and systems may similarly interactwith family members and caretakers acting on behalf of the patient,and/or outside the context of medical care. Thus, for example,notifications described herein may be provided to a caregiver or familymember so that the caregiver or family member may take an appropriateaction, if needed, thereby reducing the incidence of avoidable adverseevents.

An aspect of the disclosure relates to converting a healthcare/treatment document to interactive speech (and/or text) sessions,accessing patient data (e.g., demographics, name, medical conditions,etc.), verifying that the patient care instructions do not violate otherpatient care instructions and/or one or more protocols, receiving speech(and/or text) queries from the patient regarding the patient caredocument, and utilizing the document, patient data, and/or rules toprovide a personalized verbal response to the patient. A naturallanguage processing (NLP) engine may be utilized to accurately extractthe entities (activities) and the time points within a given protocoldocument to transform the static instructions into computable files. Theextracted entities and time points may be then transformed into aninteractive, personalized, voice-enabled model (e.g., comprising programcode stored in a file) utilizing a rules engine and a personalizationengine, and optionally the current date and/or time (accessed from alocal or remote clock device). The rules engine applies clinical rules(e.g., from evidence-based clinical decision support systems that arebased on current standards of care). The personalization engine utilizespatient information (e.g., from the patient's clinical record,onboarding assessments, updated assessments, behaviors, and/or otherpatient data disclosed herein) to reduce the need for patientmodification and interpretation of the patient's instructions. Thepersonalized, voice-enabled model may provide more accurate, natural,and clear responses as compared to conventional voice interactionsystems that use the same interaction model for large numbers of users.

For example, the personalized, customized interaction model may begenerated based on a patient's profile. The profile may be generatedusing patient responses to certain questions, family members' responsesto certain questions, caretaker responses to certain questions, and/ormedical service providers' (e.g., physicians') responses to certainquestions. The responses may be provided during an onboarding processand/or thereafter. There may be multiple types of onboarding. Forexample, there may be a first type of onboarding for a patient, and asecond type of onboarding for someone involved in the patient's care.The responses may be utilized to assess the patient's level ofengagement, preferences, motivations and beliefs.

By way of illustrative example, the patient may be asked to answer oneor more questions whose answers may indicate how much information thepatient wants regarding the patient's medical treatment, the degree towhich the patient feels accountable for his/her own care, how much thepatient relies on others for guidance in following instructions in apatient care document, how often the patient wants the system to askcertain questions, etc. The patient profile may also be based on logsindicating how often the patient utilizes the system, how many questionsthe patient asks per session and/or per time period (e.g., how manyquestions the patient asks per day, per week, per month, and/or othertime period), what times of day the patient typically asks questions,how often the patient asks the same or similar question, how often thepatient asks follow up questions after receiving an answer to aquestion, how long the interactive speech sessions typically last, howoften or quickly the patient interrupts the response before it'scompleted. The patient profile may also be based on the patient'sinterests, hobbies, level of education, language comprehension, and/orpersonality (e.g., formal or informal, jokey or serious, etc.).

The patient profile may also be based on clinical information (e.g.,electronic patient medical health records, patient-reported symptoms,medical providers' notes, demographics (e.g., age, gender, race), otherinformation that may be relevant in determining potential drug sideeffects, normal/typical lab values, etc.).

Based on the patient profile, the customized interaction model may beconfigured to provide certain level of detail in responses to patientqueries, use a certain level of vocabulary (e.g., 4th grade level, 8thgrade level, high school level, college level, etc.) in responses topatient queries, use a certain level of formality in responses topatient queries (e.g., calling the patient by a nickname, or “Mr.Smith”, “Ms. Jones,” etc.), and/or provide certain types and/or amountsof ancillary content (e.g., jokes, aphorisms, interesting facts,historical information on drugs or medical procedures the patient has orwill undergo, etc.) of interest to the patient, by way of example. Thus,utilization of the customized interaction model avoids the flood ofirrelevant data that is typically generated and provided through aconventional online search or via interaction with a conventionalchatbot.

In addition, an aspect of this disclosure relates to a machine learningengine that utilizes machine learning to generate an adaptive,multi-dimensional profile of a given patient to further enhance therelevance, accuracy, naturalness, and clarity of responses. Optionally alearning engine is utilized to build, revise, or augment a patientprofile based in part on a patient's behavior during interactive speechsessions. For example, the learning engine may be configured to modifyresponses to a patient's queries based at least in part on the behaviorof the patient with respect to previous responses.

By way of illustration, the system may respond to an initial patientquestion regarding what medication the patient should be currentlytaking. The system may provide a verbal response including the types,quantities, and times of day the patient should be taking medication,and may provide additional information such as what each medication isspecifically intended to treat, medication side effects, and the like.If the patient interrupts the system while such additional informationis being provided and asks the system to stop (e.g., terminates thesession), the system may infer that the patient only wants the specificquery answered, without additional information. On the other hand, ifthe system provides a certain level of information, but the patient hasfollow-up queries asking for still additional information, the systemmay infer that the patient appreciates in-depth information. Suchpatient behaviors may be used in dynamically determining the amount ofinformation to be provided to the patient for further queries.

The interaction model may optionally be updated in response to detectinga new diagnosis, a new prescription, a change in the patient's drugregimen, a new care plan, a newly scheduled surgery, a newly performedsurgery, a newly scheduled test, and/or receipt of new lab or testsresults to further enhance the accuracy and clarity of communicationsgenerated using the interaction model. The interaction model mayoptionally also be updated periodically (e.g., once a day, once a month,once every two months, once every sixth months, once a year, or othertime period, where the time period may a fixed time period or maychange). For example, the patient and/or other users (e.g., caregivers,family members, etc.) may optionally be asked the same questions (or asubset thereof) to identify changes from a known baseline, and when suchchanges are detected, the model may be accordingly updated. Optionally,certain simple generic questions (not specific to the patient's medicalcondition) may be asked on a daily or weekly basis, such as “how do youfeel on scale of 1-10?”. Optionally, in addition or instead, certainspecific questions relative to the patient's medical treatment protocolmay be asked on a daily or weekly basis based on an expected change incondition (e.g., “on a scale of 1-10, what is the range of motion ofyour lower leg?”).

Optionally, the system may enable the patient (or other authorized user,such as a caretaker or family member) to instruct the system to keeptrack of an identified issue (e.g., “Keep track of how I am feeling eachday,” “Keep track of my level of engagement,” “Keep track of what I careabout,” etc.). Where appropriate, the system may generate correspondingquestions for the patient, and ask the questions at a period specifiedby the tracking instructions (e.g., “Keep track of how I am feeling eachday,” “Ask me about my arms range of motion once a week”) or atintervals determined by the system (e.g., twice a day, daily, everyother day, weekly, etc.). The intervals may be determined by the systembased on the issue being tracked. For example, if the user asks that arange of arm motion be tracked, the system may set the interval to beweekly. If the user asks that patient nausea be tracked, the system mayset the interval to be twice a day. A lookup table may be definedmapping intervals to medical issues.

Patent data may also be received from IoT (Internet of Things) devices,such as wearables or other sensors that measure and/or track heart rate,exercise, glucose levels, blood pressure, and/or the like.

Responses to queries and/or other patient data (e.g., including medicalhistory data, such as procedures, tests, results, drugs, etc.) may beshared by the system with the patient, caretakers, family members,and/or medical service providers, as appropriate. Further, such patientdata may be automatically populated into the patient's electronic healthcare records maintained by one or more doctors. For example, by sharingsuch thorough and accurate medical data with medical service providers,medical service providers are provided with better visibility intopatients' status between visits. Further, sharing such data facilitatesobtaining a second opinion from a new physician or onboarding a newphysician without patients having to maintain their medical informationthemselves. Thus, an aspect of this disclosure relates to systems andmethods for providing a medical service provider with a consolidatedpatient history (e.g., via an application or browser accessiblewebsite). The consolidated patient history may be transmitted orsecurely transmitted to a designated destination.

An aspect of this disclosure relates to analyzing patient data (e.g.,treatment plans, drug prescriptions, over the counter medications,supplements, scheduled medical procedures, scheduled medical tests,patient symptoms/responses, recreational habits (e.g., drugs, alcohol),and/or other data), and accessing evidence-based clinical decisionsupport data to detect potentially harmful interactions (e.g., that mayhave been missed by the patient's medical treatment service providers(e.g., physician, dentist, pharmacist, optometrist, therapist,nurse-practitioner, nurse, etc.)).

The severity of the potential adverse interaction may be determined. Ifmore than one potential adverse interaction is identified, the relativeseverity of each may be utilized in assigning priorities to eachpotential adverse interaction. In response to detecting such potentiallyharmful interactions, an alert may be generated and provided to thepatient, family member(s), and/or caregiver(s) in the form of a specificquestion to ask a specific medical treatment service provider forclarification or correction. The alert may be provided via anotification service on a user device (e.g., smart phone, smart speaker,tablet computer, other computer, etc.), via email, or SMS/MMS message,an application, and/or otherwise. The alert may describe the potentialadverse interaction, indicate the potential severity of the potentialadverse interaction, and may provide a list of potential adverseinteractions in ranked order. Thus, the system may identify the exactissues, prioritize the issues at least in part by severity, and directthe user to the specific medical treatment service provider(s) whocan/should address each issue.

An aspect of this disclosure relates to analyzing patient data (e.g.,treatment plans, drug prescriptions, electronic calendar entries, overthe counter medications, supplements, scheduled medical procedures,scheduled medical tests, patient symptoms/responses, recreational habits(e.g., drugs, alcohol), and/or other data), and identifying specificactivities such as future appointments, notices to arrange futureappointments, pre-op/pre-procedure instructions (e.g., no water 12 hoursbefore procedure, or when to discontinue a blood-thinner prior tosurgery). In response to such identification, a notification/remindermay be generated at various times leading up to the event (e.g., a weekprior, a day prior, and the day of the event) to remind the patient (orother user). The reminders may be provided via a networked voiceassistance device (e.g., a networked speaker) utilizing a text-to-speechsystem, as described elsewhere herein. The reminder may be provided viaa notification service on other user devices (e.g., smart phone, tabletcomputer, other computer, etc.), via email, or SMS/MMS message, anapplication, and/or otherwise. The disclosed system may provide suchreminders at the appropriate time in response to a user instruction,such as the examples provided below:

-   -   Tell me when to take my drugs    -   Tell me when to perform specific tasks    -   Tell me when to see my medical service providers    -   Tell me when to schedule a new appointment

Thus, the system may set reminders for the patient to remind the patientto take specific drugs at specific times as needed. The reminders areoptionally set as alarms in order to activate the user device (e.g.,smart networked speaker) and/or associated speech-to-text system withoutthe patient having to trigger the system with the “Awake” phrase orcontrol.

An aspect of this disclosure relates to detecting when a prescriptionneeds to be refilled and generating a corresponding notification.Optionally, retail pharmacy applications and/or other pharmacy datasources are accessed, and the system detects when each of the patient'sprescriptions were filled, how many pills (or how much liquid or powder)were dispensed and when it needs to be refilled. When the system detectsthat the patient has less than a specified threshold amount remaining(e.g., a 1 week or less remaining supply), a notification may begenerated asking the patient (or other user, such as a caregiver orfamily member) if the patient wants to refill the drug. The patient mayinstruct (e.g., via voice, text, clicking on a reorder control displayedby an app, and/or the like) the system to refill the drug (e.g., “Yes,reorder ______ my prescription”) and the system will transmit acorresponding electronic refill instruction to the pharmacy system. Thesystem may also detect, via information accessed from the pharmacysystem at which the refill order was placed, when the drug is ready forpickup, the pharmacy address, and the hours of operation. Suchnotifications may be similarly provided for non-prescription drugs,supplements or other supplies that are used on a regular basis.

The foregoing notifications may be provided to the patient, caregiver,and/or family member via the smart network speaker or via a notificationservice on other user devices (e.g., smart phone, tablet computer, othercomputer, etc.), via email, or SMS/MMS message, an application, and/orotherwise. Alerts and/or other actions may be generated when the systemdetects (e.g., from internal data and/or from data accessed from apharmacy system) that drugs/supplies have not been re-ordered,delivered, or picked up. Thus, when notifications are provided to acaregiver or family member, the caregiver or family member may take anappropriate action (e.g., re-order or pickup medication, visit orcontact patient, etc.) if the patient has failed to do so.

Optionally, the system enables a user to add, via a voice or textcommand, a non-prescription drug or supply to the patient's medicinelist. Optionally, the system will detect conflicts with othermedications or procedure and generate a corresponding alert.

An aspect of this disclosure relates to sharing patient data withauthorized family members and/or caretakers. As discussed elsewhereherein, patient data is captured, and such data may be convenientlyorganized and presented in a way that the caregiver can easily retrievespecific items of data and receive automatic alerts regarding actionsthat require attention. The system may prioritize the actions based onpotential severity and optionally enables users (e.g., caregivers andfamily members) to set their own threshold levels with respect toseverity levels (e.g., non-critical, moderately important, critical, acritical level on a scale of 1-10, etc.) and corresponding notificationsto make sure they are not overwhelmed with minor alerts and actions, butcan instead focus on alerts and actions that are sufficiently important.Further, this ensures that authorized caregivers and family members areproactively informed of actions that need to be taken to preventavoidable adverse outcomes. In addition, caregivers and family areprovided with accurate medical data and enhanced visibility into theday-to-day status of the patient (e.g., using data collection fromdoctors and status information provided by the patient in response tosystem queries).

Certain aspects will now be discussed with reference to the figures.

With reference to FIG. 1, optionally, the disclosed voice interactionsystem 108 may be integrated with and utilize a third party voiceassistance terminal devices 104-1, 104-2 . . . 104-n (e.g., networkedspeakers that may include a display) and one or more third partyspeech-to-text systems 110, such as those offered by AMAZON, GOOGLE,APPLE, and MICROSOFT. Optionally, the speech-to-text system 110 may beoperated by the same entity as the interaction system 108 and optionallythe speech-to-text systems 110 may be integrated into the voiceinteraction system 108.

For example, the instant voice interaction system 108 may be a webservice hosted on a cloud system comprising a plurality of servers. Thecloud system may be associated with the provider of the third partydevice and/or speech-to-text system 110, or the cloud system may beindependent of such provider. The voice interaction system 108 maycommunicate with the speech-to-text system 110 via an applicationprogramming interface. The patient's query is streamed from the deviceto the speech-to-text system 110. The speech-to-text system 110 utilizesmapping information to determine what intent the request corresponds to.The speech-to-text system 110 may structure the request and transmit thestructured request to the interaction system 108. The voice interactionsystem 108 may also communicate with one or medical record systems 112(e.g., to access electronic patient health records, including clinicalinformation), and one/or more medical clinical decision support systems114 (e.g., that provide protocols and evidence-based recommendations forpatient treatment based on current standards of care).

As discussed elsewhere herein, interaction system 108 may be configuredto answer various user questions regarding protocols, interactions,encounters, drugs, refills, etc. The interaction system 108 may also beconfigured to ask the patient medical status information (e.g., “How areyou feeling?”, “What is your range of arm motion?”, “On a scale of 1-10,what is your pain level?”, etc.). In addition, the interaction system108 may be configured to generate alerts, set alarms, trackprescriptions, and the like.

By way of illustration, the interaction system 108 may be configured toanswer some or all of the following non-limiting example questionsregarding interactions, protocols, and encounters:

-   -   What is the purpose of Drug A?    -   What are the side effects of Drug A?    -   What interactions does Drug A have with other prescription drugs        I am taking?    -   What interactions does Drug A have with non-prescription drugs?    -   What interactions does Drug A have with alcohol?    -   What interactions does Drug A have with recreational drugs?    -   What recreational drugs am I prohibited from taking while taking        Drug A?    -   When am I permitted to take a bath?    -   When am I permitted to take a shower?    -   When am I permitted to take exercise?    -   When am I permitted to take exercise?    -   What medicine should I be taking?    -   What exercise should I be performing?    -   When should I reorder medicine?    -   When am I supposed to see the doctor?    -   What is this test for?    -   What is this procedure for, and what can I expect?    -   How should I prepare for the procedure?    -   What happens if I miss my appointment?

Optionally, the voice interaction system 108 may also communicate withusers (e.g., patients, family members, caretakers, medical serviceproviders) via applications installed on respective user terminals 106-1. . . 106-n (e.g., smart phones, tablet computers, laptop computers,desktop computers, wearables, networked televisions, etc.) and/or viawebpages accessed via respective browsers. For example, the applicationmay be utilized to communicate with the voice interaction system 108 viatext or voice, to present alerts to the user, to set user-specifiedalert-thresholds, to order medical supplies, to access and present a logof patient voice and/or text communications with the voice interactionsystem 108, and/or to provide analysis information generated by thevoice interaction system 108.

By way of illustration, the voice interaction system 108 may analyze thepatient's interaction with the voice interaction system 108, and reportinformation to the application indicating some or all of the followingexample information: what questions the patient has repeatedly askedmore than a specified threshold number of times, the average or mediannumber of questions the patient asks per session, the average or mediannumber of follow-up questions (e.g., asking for more detailedinformation than provided in a previous response) the patient asks persession, the average or median number of questions the patient asks perspecified time period, how often the patient accesses the voiceinteraction system 108 over a given time period, and/or the like.

By way of further example, the voice interaction system 108 optionallymonitors queries from a patient and determines whether there arerecurring patterns of queries and/or whether there have been no or fewqueries (which may indicate non-use or limited use of the system). Suchqueries may be timestamped with the time that the query was received.Similarly, the voice interaction system 108 may examine various timeperiods (e.g., every hour, 6 AM-9 AM, 9 AM-12 PM, 12 PM-3 PM, 3 PM-6 PM,6 PM-9 PM, 9 PM-12 AM, etc.) and based on the number of queries (or lackthereof) may take one or more predefined or dynamically determinedactions. For example, if a patient asks several times in the samemorning what medicine the patient is supposed to take (even if thepatient utilizes different language or phrases in asking the question),this may be indicative of the patient being generally confused and somay be used to trigger a follow-up by the physician and/or a caregiverto determine the mental and/or health status of the patient.

The speech-to-text system 110 may receive a voice communication from auser (e.g., patient, caregiver, family member, etc.), and use a naturallanguage processing engine to translate the speech to text. The text maybe analyzed to determine if the user is invoking a “skill” and/or theuser's “intent” (e.g., what a user is trying to accomplish, which maycorrespond to a service the user is requesting).

A skill may be an application (or “app”) configured to work with thevoice assistance device and the speech-to-text system. The applicationmay optionally be hosted on servers associated with the speech-to-textsystem operator. The skill may be enabled by a user so that the user canaccess the skill. For example, the skill may be enabled via anapplication or via a voice instruction provided by the user using thevoice assistance device. The skill may provide services corresponding tothe intents. Although the following discussion utilizes terminologyassociated with AMAZON's ALEXA device and service, the discussionsimilarly applies to other platforms, such as GOOGLE's HOME device andservice (which refers to apps as “actions” rather than “skills”, andrefers to the web service that can fulfill an intent as “fulfillment”).The services associated with the such devices may utilize respectiveinteraction models, which may optionally be distinct from thepersonalized interaction models discussed elsewhere herein.

For example, sample words and phrases may be defined to indicatecorresponding intents. By way of illustration, a mapping of words andphrases to intents may be generated and used to determine the user'sintent. A given intent may have one or more associated variables(sometimes referred to as slot values) which are passed to the intent,such as the name of a medicine a user is inquiring about. Thus, forexample, a medicine variable may be associated with a list of medicinesprescribed for a given patient. By way of further example, an exercisevariable may be associated with a list of exercises prescribed for agiven patient. By way of yet further example, a diagnoses variable maybe associated with a list of diagnosis prescribed for a given patient.By way of still further example, a proscribed food variable may beassociated with a list of foods proscribed for a given patient.

Optionally, the system may utilize third party built-in intents (withassociated mappings to utterances) when utilizing a third party userterminal and speech-to-text system, such as the ALEXA platform providedby AMAZON. For example, certain intents may be commonly used bydifferent skill providers, such as “Help”, “Yes”, “No”, “Stop”,“Repeat,” “Pause”, “Resume”, etc. The use of such built-in intentsenables users to engage with different skills from different providersusing consistent language.

A user may need to state a wake phrase (e.g., hey you, gizmo, “Acme”,“Alexa”, “OK Google”, “hey Siri”, etc.) prior to submitting a request(e.g., a query or instruction), in order to inform the terminal 104 orspeech-to-text system 110 that a request is being provided by thepatient (or other user) to the system.

The wake phrase may include one or more triggers words or otherexpressions (e.g., clapping of hands or a whistle). Optionally, ratherthan utilizing a wake phrase, a physical or touchscreen control may beutilized. In addition, a user may need to state an invocation phrase(e.g., “Frontive”) to invoke a skill (e.g., provided by the voiceinteraction system 108). Optionally, in certain implementations, a wakephrase is not needed, and the voice assistant device may “wake” itself(or be woken by the voice interaction system 108 or the speech-to-textsystem 110), and push information or queries. By not needing a wakeword, the voice interaction system 108 may initiate voice communicationsto the patient (or other user). By way of example, the voice interactionsystem 108 may automatically direct the user to take a certain action(e.g., “it's time to take your amoxicillin now”), or provide a voicenotification (e.g., “your Celebrex refill will be ready for pickup at 3PM today”), without the user providing a wake phrase.

Thus, for example, if a patient wanted to ask if he is permitted todrink alcohol, the patient might state “Acme, ask Frontive, if I candrink wine.” In the forgoing phrase, “Acme” is the wake phrase,“Frontive” is the invocation phrase for the Frontive skill (provided bythe voice interaction system 108), “can drink” is the intent, and “wine”is the variable.

Thus, by way of further example, if there is an intent used with respectto identifying proscribed foods (“ProscribedFoods”), the followingutterances may be mapped to the “ProscribedFoods” intent, and used toinvoke the intent:

-   -   “When can I drink (food name)”    -   “Can I drink (food name)”    -   “Can I have a (food name)”    -   “Can I eat (food name)”    -   “Is it ok to eat (food name)”

When a user request (which may be an instruction or query) is receivedvia a third party NLP system, such as that provided by thespeech-to-text system 110, the speech-to-text system 110 may assign aunique identifier to the service associated with the skill (“Frontive”in this example). The speech-to-text system 110 may include the uniqueidentifier when passing a user request to a corresponding service. Uponreceipt by the voice interaction system 108, the service may verify theunique identifier is that assigned to the service, and if not, theservice may transmit an error message to the speech-to-text system 110and/or not further process the user request. By declining to processrequests that do not have the correct skill identifier, processingresources are conserved.

In addition, a unique user identifier that identifies the user makingthe requested may be appended to the request. The user identifier may beautomatically generated when the user enables the skill (“Frontive” inthis example). Optionally, a timestamp indicating when the request wasmade may be appended to the request. Optionally, a unique requestidentifier may be generated and appended to the request.

Thus, when a request is received by the speech-to-text system 110, itmay identify the intent (from the intent to utterances mapping) and anyvariable values, and transmit the intent, the variable values, theunique skill identifier, the unique user identifier, and the timestampto the service hosted by the voice interaction system 108. The servicemay verify that the request is intended for the service and use theunique user identifier to locate and access the appropriate personalizedmodel, medical records, profile, and/or other information associatedwith the user. The service may then process the request and provide anappropriate response.

A given session with a user may include more than one request. A usermay explicitly end a session by speaking a termination phrase (e.g.,“bye {invocation phrase}”, “terminate”, “exit”, “all done”, and/or otherphrases).

If a user states the skill invocation phrase (“Frontive” in thisexample) without an utterance that is mapped to an intent (e.g., “I havequestions for Frontive”), the service may generate a response, statingthat more information is needed from the user, or listing availableintents (or a subset thereof, such as the 4 most common requests fromusers, or the 4 most common requests from the specific user currentlymaking the request). For example, the voice interaction system 108 mayrespond with the following “Did you want to ask about when you shouldtake your medications, when is your next doctor's appointment, when canyou take a bath, or something else?”.

If the skill needs more information to complete a request, the voiceinteraction system 108 may conduct an interactive conversation with theuser. For example, if the user asks “when does Frontive say I can stoptaking medicine”, without specifying the medicine being referred to, andwhere the patient is taking more than one medication, the voiceinteraction system 108 conduct the following conversation with the user:

Voice interaction system 108: “Which medicine are you asking about”

User: azithromycin

Voice interaction system 108: “You can stop taking azithromycin in threedays, on April 28”

FIG. 2 illustrates certain components of an example voice assistantdevice 104. A device 104 may include one or more microphones 204, one ormore speaker transducers 202 (e.g., cone speakers, electrostaticspeakers, dome speakers, etc.), a digital media processor 210 (e.g.,comprising a microprocessor, an audio processor, a visualinterface/graphics processor, a memory controller, internal RAM,internal ROM), volatile memory 212 (e.g., SDRAM), non-volatile memory214 (e.g., NAND Flash Memory), a wireless interface 216 (e.g., WiFiinterface, a Bluetooth interface, a 4G cellular interface, a 5G cellularinterface, etc.), a power management circuit 218, a digital-to-analogconverter 206 (to convert digital information, such as digital voicedata from the interactive system 108, to the analog domain to drive thespeaker transducers), an analog-to-digital converter 208 (to convertanalog information, such as voice signals from the microphones 204, tothe digital domain for transmission to the interactive system 108)), apower supply (not shown), a visual user interface 220 (e.g., LEDindicator lights, LCD display, OLED display, e-ink display, etc.),and/or the like. The speaker transducers 202 may include woofer speakerelements, midrange speaker elements, tweeter speaker elements, and/orother speaker elements.

FIG. 3 illustrates an example implementation of the voice interactivesystem 108. The example interactive system 108 includes a data store ofpatient profile information (e.g., health information accessed fromelectronic health records, information received via patient input,received from sensors (e.g., wearables or other devices) that measureuser parameters (e.g., blood pressure, heart rate, glucose levels,etc.), received via caretaker input, via family member input, viamedical service provider input, from pharmacies, etc.). In addition, theinteractive system 108 includes a personalization engine used togenerate an interactive model, as discussed elsewhere herein. A naturallanguage processing engine 310 is provided which may perform opticalcharacter recognition (e.g., on patient care/protocol documents), syntaxanalysis (e.g., morphological segmentation, part-of-speech tagging,parsing using a parse tree, sentence boundary disambiguation, wordsegmentation), semantics analysis (e.g., lexical semantics, named entityrecognition, natural language understanding, relationship extraction,sentiment analysis, topic recognition and segmentation, stemming, wordsense disambiguation, tokenizing, etc.), discourse analysis,co-reference resolution, automatic summarization, etc. The naturallanguage processing engine 310 may also be utilized to produce naturalsounding responses to requests using natural language generation thatconverts data into a natural language representation (e.g., usingcontent determination (e.g., to determine what content, and what levelof detail, is to be included), document structuring (e.g., to organizeinformation provided in a response to a user query in a way to clearlyconvey the information), aggregation (e.g., the aggregation of similarinformation or sentences to improve the naturalness andunderstandability of responses), lexical choice, referring expressiongeneration (that identifies objects and/or regions), and realization(e.g., creation of the actual response in accordance with propergrammar, syntax rules, orthography, and morphology).

A machine learning system 312 may be provided that is utilized toimprove the performance of the natural language processing engine 312and to improve the performance of the personalization engine 308. Themachine learning system 312 may include one or more machine deeplearning engines. The machine learning system 312 may analyze userinteractions and utilize such analysis to improve the performance of thenatural language processing engine 312 and/or the personalization engine308.

The interactive system 108 may include a voice assistant interface 302(e.g., to communicate with smart speakers and/or other voice systems)and a companion application interface 304 to interface with applications(such as those described herein) on user devices.

An example process for generating a personalized interaction model willnow be described with reference to FIG. 4. As noted above, thepersonalized interaction model is configured to provide information in amanner suitable for the particular patient, and in a manner to make thepatient more inclined to want to interact with the interaction system.Questions may be provided (e.g., via device 104, an application, awebpage, and/or otherwise) configured to extract information regardingthe patient's personality (e.g., optimistic, pessimistic, upbeat,negative, etc.), the strength of the patient's motivation in self-care,one or more goals that are driving the patient (e.g., attending anupcoming event such as a reunion or family vacation), how much thepatient relies on others for guidance in following instructions in apatient care document, the patient's desire for detailed informationregarding medical matters, the sophistication of the patient'svocabulary (e.g., 4^(th) grade level, 8^(th) grade level, high schoollevel, college level, other grade level, etc.), the patient's ability tocomprehend medically-related information, the patient's ability toretain medically-related information, the patient's sense of humor(e.g., does the patient like jokes or clever repartee, or is the patientvery serious), the subjects the patient is interested in (e.g.,specified hobbies, sports, music, history, science, technology, art,literature, video games, movies, television, news, celebrities,religion, philosophy, medicine, geography, politics, cars, etc.), thepatient's recreational habits (e.g., recreational drugs, alcohol), thepatient's family situation (e.g., married, single, living alone, livingwith spouse, living with partner, how many children, how many childrenliving at home, how many children living within a specified nearbygeographical area, etc.), the patient's residence (e.g., house,apartment, one story residence, two story residence, stairs, etc.),demographics (e.g., age, gender, race, income, etc.), information fromsensors (e.g., wearables, glucose sensors, or other devices) thatmeasures user parameters (e.g., blood pressure, heart rate, oxygenlevels, glucose levels, etc.), and/or other information. The foregoinginformation may include explicitly provided user preferences andinformation from which the patient's preferences may be inferred.

The questions may be provided to, and responses received (e.g., via avoice assistance device, an application installed on a user device, awebsite, etc.) from the patient and/or the patient's family members,caretakers, and/or medical service providers. The questions may beprovided, and responses received, during an onboarding process (setup ofan account for the patient) and/or thereafter. For example, thequestions may be provided periodically (e.g., twice a year, once a year,once every two years, etc.) and/or in response to certain events (e.g.,the occurrence of one or more of a selected set of medical interventionsor encounters, a new health condition, a change in address, a userrequest that an update be performed, etc.), in order to ensure that thepatient profile adequately reflects the patient's current situation.

At block 402, the patient's profile information is accessed. In additionto the responses to the profile queries, if the patient has already beenutilizing the system, and the current model generation process is beingexecuted to update the model, the patient profile may be also be basedon preference inferences made using logs indicating how often thepatient utilizes the system, how many questions the patient asks persession and/or per time period (e.g., how many questions the patientasks per day, per week, per month, and/or other time period), what timesof day the patient typically asks questions, how often the patient asksthe same or similar question, how often the patient terminates a sessionwhile a response to a patient question is in the process of beingstreamed to the patient, how often the patient asks follow up questionsafter receiving an answer to a question, how long the interactive speechsessions typically last, information from sensors (e.g., wearables orother devices) that measure user parameters (e.g., blood pressure, heartrate, glucose levels, etc.), and/or the like.

At block 404, the patient's medical/health records are accessed from anelectronic medical record system. The electronic medical/health recordsmay include some or all of the following information: treatment plans(e.g., protocols), patient demographics, progress notes, vital signs,medical histories, diagnoses, medications, immunization dates,allergies, radiology images, lab and test results. Optionally, retailpharmacy applications and/or other pharmacy data sources are accessed,and the process detects when each of the patient's prescriptions werefilled, how many pills (or how much liquid or powder) were dispensed andwhen it needs to be refilled.

At block 406, patient profile information and electronic medical/healthrecord information are used to generate a customized, personalizedinteraction model for the patient. In addition, ancillary content thatthe patient may be interested may optionally be accessed and utilized ingenerating the personalized model. Optionally, information relevant toone or more protocols for the patient may be accessed from a clinicaldecision rules system and utilized to generating the model.

The personalization interaction model may define the verbal requeststhat the system will handle and the words that an end-user (e.g., apatient) may utilize in making such requests. The interaction model mayalso define what types of ancillary information (e.g., jokes, aphorisms,interesting facts, news, sports references, etc.) are to be presented tothe user and when. The interaction model may also define what questionsshould be asked of the patient (and when) to determine if the modelshould be updated. The interaction model may also define what alerts andreminders should be provided to the patient (e.g., regarding takingmedication, performing exercise, placing medication refills, preparingfor a procedure, etc.). The interaction model may also define how theuser should be referred to when speaking to the user (e.g., by firstname, nickname, using a title (Dr., Ms., Mr., Mrs., etc.), orotherwise). Once generated, the model may be utilized.

At block 408, a determination is made as to whether the model should beupdated. For example, as similarly discussed elsewhere herein, theprocess may detect (e.g., via the patient's medical records orinteractions with the patient or other users) whether there has been anew diagnosis, changes in the user's status as determined from sensorreadings (e.g., from wearables or other devices as discussed elsewhereherein), a new prescription, a change in the patient's drug regimen, anew care plan, a newly scheduled surgery, a newly performed surgery, anewly scheduled test, and/or receipt of new lab or tests results. Inresponse to such detection and corresponding update rules, the processmay decide whether or not the model is to be updated. By way of furtherexample, the process may detect whether a scheduled update date has beenreached, and if so, the process may determine that the model is to beupdated.

If a determination is made that the model is to be update, at block 410a determination is made as to whether the patient and/or other usersshould be queried regarding the patient. For example, the patient and/orother users (e.g., caregivers, family members, etc.) may optionally beasked the same questions (or a subset thereof) as asked during anonboarding process or for a previous update to identify changes from aknown baseline. In certain cases, a determination may be made that it isnot necessary to update query responses. For example, if a model updateis being performed because the patient is being switched from oneantibiotic to another antibiotic, there may be no need to providequeries to the patient, and the model may be updated utilizing priorquery responses and the new prescription. If a determination is made thequeries are to be provided, than at block 412, the queries are providedto the designated recipients (e.g., the patient, caretaker, familymember, medical service provider, etc.). The process proceeds back toblock 402, and the new (and optionally older) responses are accessed,and the process repeats to generate an updated personalized user model.

FIG. 5 illustrates an example voice session process which may beperformed utilizing systems and devices illustrated in FIG. 1. At block502, the user makes a voice request. In real time, the user's voice istransduced by a microphone (e.g., of voice assistant device 104) andtranslated from the analog domain to the digital domain using ananalog-to-digital converter. At block 506, the digitized voice may bestreamed in real time from the voice assistant device to aspeech-to-text system, which receives the digitized voice. At block 508,the speech-to-text system performs national language processing on thedigitized voice, and identifies the skill being invoked, the intent, andany intent variable values. At block 510, the speech-to-text systemgenerates a structured request indicating the intent and variablevalues. The system may transmit the structured request to a voiceinteractive system. The request may include a unique skill identifier, aunique user identifier, and a timestamp indicating when the request wasmade.

At block 512, the voice interactive system processes the user requestand generates a personalized response utilizing a personalizedinteraction model (e.g., where the model is generated using processesdiscussed herein). At block 514, the process provides the response to atext-to-speech system, which converts the response into a formatsuitable for the voice assistant device. At block 516, the response isstreamed to the voice assistance device. At block 518, the voiceassistant device converts the received response to an analog signalusing a digital-to-analog converter. At block 520, the voice assistantdevice utilizes the analog signal to drive one or more speakers, therebyproviding a voice output. It is understood that several of the aboveoperations may overlap with each other.

FIG. 6 illustrates an example response generation process, correspondingto block 512 in FIG. 5. At block 602, receives a structured requestindicating the intent and variable values. The process analyzes theskill identifier to determine that the request is intended for theresponse generation process. If the skill identifier is correct, theprocess utilizes the unique user identifier to identify and retrieve thepersonalized interaction model for the user and to access health recordsfor the user. The process identifies if there is a time componentassociated with the request. For example, certain requests, such asthose that ask if the user can engage in certain activities in the nexttwo weeks, the time element is specific. If, on the other hand, therequest asks if the user can engage in certain activities (withoutspecifying a time period), the process may infer that the request isrelated to the current time. By yet further example, certain requestsmay have no explicit or inferred time element. For example, if therequest is regarding what a medication is used for, the response will beindependent of any time period.

At block 606, the received intent is mapped to responses. For example,if the intent is regarding proscribed foods (e.g., the request is “Whatfoods must I avoid”), the response may be “You cannot have” (list ofproscribed foods). At block 608, any applicable variable values are usedto populate corresponding response variables. For example, if the userasked “What medications should I take this morning”, the response may be“This morning you should take the following medications:{medication.names},” where medication.names is a variable. The processmay determine what medications the user is to take the current morning,and populate the response accordingly. At block 610, the final responseis generated, which may include content not specific to the request andmay include personalization content (e.g., “Good morning Liza! Thismorning you should take the following medications: one pill of Celebrex.Also, I know you like vegetables, so keep in mind that leafy greens likespinach and kale may help curb inflammation!”).

FIG. 7 illustrates an example process for parsing a care plan, which mayprovide a protocol for treating a health issue, such as post-operationalcare. At block 702, a care plan is accessed. At block 704 the processutilizes natural language processing (NLP) to identify prescribedmedications and associated time elements (e.g., what medications and thequantity of each medication the user is supposed to take each day orweek). At block 706, the process utilizes NLP to identify proscribedmedications and associated time elements (what periods of time thepatient should not take the proscribed medications). At block 708, theprocess utilizes NLP identify prescribed physical activities andassociated time elements (when the patient is to perform the prescribedphysical activities). At block 710, the process utilizes NLP to identifyproscribed physical activities and associated time elements (when thepatient is not to perform the proscribed physical activities). At block712, the process utilizes NLP to identify prescribed activitiesconditioned on physical status (e.g., where if the patient no longerfeels pain, the user may be permitted to engage in certain physicalactivities). At block 714, the process utilizes NLP to identifyprojected health status/goals (e.g., degrees of movement, reduction inpain, increase in strength, etc.) and associated time elements. At block716, the process utilizes NLP to identify appointments (e.g., withphysicians, nurses, physical therapists, etc.) and associated timeelements. At block 718, the process utilizes NLP to identifyself-inspection instructions and associated time elements.

FIG. 8 illustrates an example process for detecting care plan conflicts.At block 802, the process accesses one or more care documents from oneor more medical service providers. At block 804, the process accessesone or more clinical decision support systems that provide rules andguidelines with respect to medical treatments and protocols. At block806, the process utilizes the rules and guidelines from the clinicaldecision support systems to determine if there are any conflicts (e.g.,adverse interactions) within a care document or between two or more caredocuments. Thus, for example, potential adverse drug-drug interactions,drug-lifestyle interactions, drug-procedure interactions, and unusual oralarming responses to drugs or a procedure may be identified.

For example, a first patient care document may indicate that the patientis to take a first medication and a second patient care document mayindicate that the patient is to take a second medication, where thesecond medication in combination with the first medication will have anadverse effect on the patient (e.g., as determined from rules accessedfrom a clinical support system). By way of further example, a firstpatient care document may indicate that the patient is to eat a certainamount of a first food each day, while a second patient care documentmay indicate that the patient is to fast a day before a specifiedprocedure.

Optionally, logically incompatible instructions may be identified indetecting a conflict (e.g., where one instruction indicates that thepatient is to fast and another instruction says the patient is to eatthree balanced meals; or where one instruction says to stay in bed andanother instruction says to go on a 30 minute walk).

At block 808, the severity of the potential conflict may be determined.At block 810, if more than one potential conflict is identified, therelative severity of each may be utilized in assigning priorities toeach potential conflict. At block 812, in response to detecting suchpotentially harmful interactions, an alert may be generated and providedto the patient, family member(s), and/or caregiver(s) in the form of aspecific question to ask a specific medical treatment service providerfor clarification or correction. The alert may be provided via anotification service on a user device (e.g., smart phone, smartnetworked speaker, tablet computer, other computer, etc.), via email, orSMS/MMS message, an application, and/or otherwise. The alert mayindicate the potential severity of the potential conflict, and mayprovide a list of potential conflicts in ranked order. Thus, the processmay identify the exact issues, prioritize the issues by severity, anddirect the user to the specific medical treatment service provider(s)who can/should address each issue. Optionally, when a conflict isdetected, the system may attempt to resolve the conflict.

Non-limiting examples of alerts are as follows:

-   -   Ask Dr. Acme about the interaction of Drug A with Drug B.    -   Ask Dr. Beta about the interaction of Drug A with upcoming        medical procedure B interactions    -   Ask Dr. Gamma about your increase in heart rate when you take        Drug A    -   Ask Dr. Delta about the interaction of Drug A with drinking        alcohol to smoking marijuana

As noted above, the system may optionally attempt to resolve theconflict using clinically-validated rules. For example, if the systemdetermines that the user is to fast the day of a surgery, the system mayoptionally automatically determine, using clinically-validated rules,that the fasting takes precedence for at least the day of the surgeryover any instructions regarding eating a well-balanced meal.

FIGS. 9-11 illustrate an example voice interaction system architectureand related processes. As illustrated in FIG. 9, the voice interactionsystem architecture may include an onboarding/report generator server902 (although the onboarding module may be hosted on a different serverthan the report generator server), a personalization engine and datastore 904, a security authorization module 906, a query resolver 908,and a medical records store 912. The onboarding server/report generator902 may communicate with various user devices, such as a smart phone,tablet, smart television or other device, via a dedicated applicationand/or a browser. A voice assistant device 910, such as that describedelsewhere herein (e.g., a smart speaker), may communicate with the voiceinteraction system.

At state 9A, a user is authenticated and a session is enabled by thesecurity authorization module 906. For example, the authentication maybe performed by the user speaking a code provided to or created by theuser and comparing the spoken code with that associated with the user todetermine if there is a match, and if there is a match, the user isauthenticated and a session is enabled. By way of optional example, thecode may be transmitted by the system to the user via email, SMS, orotherwise. The code may have been provided or generated during aninitial onboarding process, such as that described elsewhere herein.

Optionally, in addition or instead, the authentication may be performedutilizing voice print analysis, wherein characteristics of a speaker'svoice are used to identify the speaker or verify the speaker is who heis represented to be. For example, if a household has multiple members,speaker verification may be performed to verify the speaker is theregistered user and not another family member. The user may undergo avoice enrollment procedure (e.g., during an onboarding process or atanother time), where the user's voice is recorded and certain features(e.g., dominant tones) are extracted to form a voiceprint (e.g., a voicemodel) of the user. Optionally, the user may be provided with a writtenand/or oral script that the user is to orally rebate as part of theenrollment process.

The user voiceprint may be stored in association with the user's accountand data. When the user later wants to interact with the system (e.g.,using the voice assistant device 910), an authentication process may beperformed. During authentication, a user voice input (e.g., word orphrase) may be compared with the previously created voiceprint.Optionally, the user is prompted via the voice assistant device 910 torepeat a phrase of one or more specified words (e.g., those the userspoke during the enrollment process) to provide the voice input to speedup the authentication process and make it more accurate. Optionally, theuser may utilize speech of the user's own choosing in providing thevoice input used in authentication to make the process easier for theuser. If the features of the user's voice input match the voiceprint,then the user is authenticated. If the features of the user's voiceinput do not match the voiceprint, then the user is not authenticatedand the user may be inhibited from accessing or utilizingpersonalization or medical data.

Optionally, a multistage authentication process may be performed. By wayof example, a user may first need to provide an audible code (e.g., averbal password), and then the system may ask the user (e.g., using thevoice assistant device 910) certain security questions for which theanswers were previously provided by the user (e.g., during an onboardingprocess) or for which answers are known from conversation interactionswith the user. For example, the system may ask the user what street shegrew up on, what her favorite sports team is, what is her primarydoctor's name, etc. The user's answer may be compared against the knownanswer, and if they match, the user is authenticated and can accessand/or utilize the personalization data (and if they do not match, theuser is not authenticated and cannot access and/or utilize thepersonalization data).

Optionally, a first level of authentication may be provided in order forthe user to interact with the system, where such interaction does notrequire access to the user's medical data but does utilizepersonalization vectors and data, and a second level where suchinteraction does require access to the user's medical data. For example,if the user is asking about the current news, is setting an alarm, or isasking a general question about a specific drug (e.g., “what are commonside effects of acebutolol”?), then no knowledge of the user's medicalcondition or treatment is needed, and so a first level of authenticationmay be performed (e.g., using a first code, a voice print, etc.). If aresponse to the user's query (e.g., “What medications am I taking,” “Howmany pills am I supposed to take”, etc.), a second level ofauthentication may be performed (e.g., using a second code, a voiceprint, a security question, etc.). Thus, advantageously, more sensitiveinformation (e.g., medical information) is optionally provided withheightened protection as compared with less sensitive information.Optionally, a security session timeout may be utilized, wherein if theuser fails to provide a verbal input for a threshold period of time, thesystem may require the user be re-authenticated using one of theauthentication techniques described herein. Optionally, the user may beable to specify the threshold period of time via a voice command or viathe companion application.

At state 9B, the security authorization module 906 unlocks and enablesthe query resolver and the personalization engine. At state 9C, adigitized user query may be received via the voice assistant device 910.The user query may be provided to the query resolver 908. The queryresolver 908 may request user data or vectors from the personalizationstore 904 and/or one or more medical record data stores 912. Publicallyavailable medical protocols may be accessed as well and are optionallytreated as medical data with respect to certain questions (e.g., “whatpills am I supposed to take this morning?”), because even though theprotocol is public document, the fact that the user is following theprotocol may not be public. A determination is optionally made as towhether a response to the query will necessitate access of the medicalrecords store 912, and if so, a second level of authentication may beperformed, as discussed above.

At state 9D, the onboarding/report generator server 902 interacts with adefined set of care providers (e.g., medical personnel, family members,etc.) and optionally the user. For example, the onboarding/reportgenerator server 902 may generate alerts if it detects that the user hasnot utilized the system for a threshold period of time. By way offurther example, if the user not placed a medication refill instructionor picked up a medication waiting for the user at a pharmacy (e.g., asdetermined by accessing information from a pharmacy computer system), anotification and/or a reminder may be generated. Optionally, thenotifications and reports may be provided to the user in addition to orinstead of to care providers. The system may optionally initiate a callbetween the user and one or more care providers (e.g., utilizing VoIP,where the user may optionally communicate via the voice assistant device910) in response to a user request and/or in response to detectingcertain specified events (e.g., the user has failed to place a refillorder for a needed medication).

FIG. 10 illustrates an example personalization workflow. In thisexample, two types of users are interacting with the personalizationworkflow, a member (e.g., a patient), and one or more people in apatient care circle 1006 (e.g., a medical service provider, caretaker,family member, etc.). Optionally, each type of user undergoes anonboarding process via the onboarding server 902. The different types ofusers may undergo different onboarding processes, asked differentquestions, and different types information may be collected fromdifferent users.

By way of further example, the member/patient may be asked during anonboarding process or thereafter to answer questions whose answers mayindicate how much information the member/patient wants regarding theuser's medical treatment, the degree to which the member/patient feelsaccountable for his/her own care, how much the member/patient relies onothers for guidance in following instructions in a user care document,how often the user member/patient accesses wants the system to askcertain questions, how the member/patient wants to be addressed (e.g.,by which name/nick name), interests, hobbies, level of education,language comprehension, and/or personality (e.g., formal or informal,jokey or serious, etc.), etc.

Someone in the care circle may be, by way of example, asked questionsabout the member/patient (which may be regarding the same matters asasked of the member/patient) and/or questions regarding the types andfrequency of information the person in the care circle would like toreceive.

The information collected via the onboarding process may be utilized bythe personalization server 904 to generate an initial preference vector.The preference vector may be utilized by the query resolver 908 asdescribed herein and to determine what dynamic content 1002 should beprovided to the member/patient 1004 or care circle user 1006.

FIG. 11 illustrates an example personalization workflow in greaterdetail. Referring to FIG. 11, a compiler 1104 receives a user preferencevector 1102 and content 1106 (e.g., dynamic content/new content, such asthe current day's news, daily jokes, facts, ribbing about the user'sfavorite sports team, etc.). The preference vector may be associatedwith a unique code corresponding to the user (member/patient or a carecircle person). The preference vector may specify multiple templates forinteracting with the user. The preference vector may be generated usingexpressly provided or inferred user preferences. For example, thepreference vector may be generated utilizing information received fromthe member/patient and/or care circle persons during one or moreonboarding processes, as similarly described elsewhere herein.

In addition, the preference vector may be updated based on the user'sinteractions with the system. For example, the interactions may includeuser queries, logs of the user's reactions to responses and otheraudible content (e.g., did the user ask a follow-up questions, did theuser laugh at a joke told by the system, when queried as to whether theuser liked an item of content (e.g., a joke, sports information, news,etc.) did the user answer yes or no, etc.).

As noted above, the user preference vector may also be based on logsindicating how often the user utilizes the system, how many questionsthe user asks per session and/or per time period (e.g., how manyquestions the user asks per day, per week, per month, and/or other timeperiod), which part of a given workflow the user used and did not use,what times of day the user typically asks questions, what questions wereasked, how often the user asks the same or similar question, how oftenthe user asks follow up questions after receiving an answer to aquestion, how long the interactive speech sessions typically last, didthe user ask for technical assistance, how often the user asked for acertain type of content (e.g., for another joke, for sports scores,stock prices, etc.), and/or how often or quickly the user interrupts theresponse before it's completed. The user's preference vector may also bebased on the user's interests, hobbies, level of education, languagecomprehension, and/or personality (e.g., formal or informal, jokey orserious, etc.).

Optionally, the user preference vector may also be based on clinicalinformation (e.g., electronic user medical health records, user-reportedsymptoms, medical providers' notes, etc.).

Using the preference vector 1102 and content 1106, the compiler 1104optionally generates a user-specific program (e.g., a Pythonprogram)/script which will be generally referred to as a script) 1108.The program/script is deployed to other portions of the voiceinteraction system 1112 (e.g., query resolver). The user can theninteract with the user-specific script using voice via the voiceassistant device 910.

Referring to FIG. 12, an example user feedback loop is illustrated. Aswill be described the feedback loop utilizes voice inputs from a user tomap user phrases to common formulas (e.g., f(x, y)), which may beutilized to determine intents, subjects, and verbs.

By way of illustration, a user may ask “what's the deal with [amedication name]?” via the device 910. However, the system may not knowhow to map the phrase to the desired intent. Such mapping failure may belogged by the logging server 1210. A word embedding module 1202 may beutilized to infer which words or whole phrases are intent synonyms. Wordembedding may utilize a dense vector representation of phrases/wordsthat try to capture the meaning of that phrase/word.

For example, words and/or whole phrases (including multiple words) maybe expressed as vectors of co-occurring words and/or whole phrases.Optionally, in addition or instead, words and/or phrases may beexpressed as vectors of linguistic contexts.

By way of further example, the vector may reflect the structure of theword/phrase in terms of morphology, word/phrase-context representation,global corpus statistics, and/or words/phrases hierarchy. The vector maybe expressed as real numbers.

The mapping may be performed utilizing one or more techniques. Forexample, a phrase/word co-occurrence matrix, a neural network (such as askip-gram neural network comprising an input layer, an output layer, andone or more hidden layers), or a probabilistic model may be utilized.Optionally, in addition to or instead of word/phrase embedding,distributional semantics models may be utilized that countco-occurrences among words by operating on co-occurrence matrices.Optionally, the mapping may be performed using a third partyspeech-to-text system, such as that described elsewhere herein. Thethird party speech-to-text system optionally only transmits an intentrequest to the voice interactive system if it is able to successfullymatch a user spoken phrase to one of a pre-configured set of intents. Ifthe third party speech-to-text system fails to map the user phase to oneof the pre-configured set of intents, optionally the third partyspeech-to-text system will not forward the user request to the voiceinteractive system. Optionally, the third party speech-to-text systemwill only transmit the intent request and any slot values captured aspart of the user utterance, and not the full user utterance (whether ornot successfully or unsuccessfully matched to an intent) to the voiceinteractive system.

By way of illustration, the process may examine words or phrases boundedby (on one or both sides) of a phrase/word at issue, and find otheroccurrence of other phrases/words with the bounding words/phrases (e.g.,in a corpus to text 1204). The process may infer that words/phrasesbounded by the same words/phrases have an equivalent meaning/intent.Optionally, stop word filtering may be performed where very common words(e.g., ‘a’, ‘the’, ‘is’, etc.) are excluded from consideration asbounding words.

By way of example, the phrases “what's the deal with [medication name]”,“can you describe [medication name]”, “tell me about [medication name]”may all be mapped to the same intent (e.g., the user wants informationregarding [medication name]).

By way of illustration, words/phrases regarding medication may be mappedto a common function, such as f(x, drug name), that describes themedication.

In addition, the feedback loop process may include asking the user ifthe user liked certain content and/or query answers provided by theuser, whether the user wants more or less information, whether the userwants to know about medication side effects, etc. Based on the user'sresponses, the user's preference profile and vector(s) may be updated.For example, if the user indicates that the user likes a first type ofcontent and does not like a second type of content, the user'spersonalization vector(s) may be updated so that the user is providedmore of the first type of content and less of a second type of content.

Thus, aspects of this disclosure relates to systems and methods thatenable patients to be provided with access to useful informationregarding their healthcare and clarify patient care instructions withintheir own home, without having to repeatedly contact their medical careservice provider. Further, aspects of this disclosure relates to systemsand methods that provide visibility and insight to patient behaviors anda patient's understanding of patient care documents to caregivers andphysicians. Further, patient satisfaction is increased, patienthealthcare is improved, while the workload on the physician andphysician infrastructure is reduced.

The methods and processes described herein may have fewer or additionalsteps or states and the steps or states may be performed in a differentorder. Not all steps or states need to be reached. The methods andprocesses described herein may be embodied in, and fully or partiallyautomated via, software code modules executed by one or more generalpurpose computers. The code modules may be stored in any type ofcomputer-readable medium or other computer storage device. Some or allof the methods may alternatively be embodied in whole or in part inspecialized computer hardware. The systems described herein mayoptionally include displays, user input devices (e.g., touchscreen,keyboard, mouse, voice recognition, etc.), network interfaces, etc.

The results of the disclosed methods may be stored in any type ofcomputer data repository, such as relational databases and flat filesystems that use volatile and/or non-volatile memory (e.g., magneticdisk storage, optical storage, EEPROM and/or solid state RAM).

The various illustrative logical blocks, modules, routines, andalgorithm steps described in connection with the embodiments disclosedherein can be implemented as electronic hardware, computer software, orcombinations of both. To clearly illustrate this interchangeability ofhardware and software, various illustrative components, blocks, modules,and steps have been described above generally in terms of theirfunctionality. Whether such functionality is implemented as hardware orsoftware depends upon the particular application and design constraintsimposed on the overall system. The described functionality can beimplemented in varying ways for each particular application, but suchimplementation decisions should not be interpreted as causing adeparture from the scope of the disclosure.

Moreover, the various illustrative logical blocks and modules describedin connection with the embodiments disclosed herein can be implementedor performed by a machine, such as a general purpose processor device, adigital signal processor (DSP), an application specific integratedcircuit (ASIC), a field programmable gate array (FPGA) or otherprogrammable logic device, discrete gate or transistor logic, discretehardware components, or any combination thereof designed to perform thefunctions described herein. A general purpose processor device can be amicroprocessor, but in the alternative, the processor device can be acontroller, microcontroller, or state machine, combinations of the same,or the like. A processor device can include electrical circuitryconfigured to process computer-executable instructions. In anotherembodiment, a processor device includes an FPGA or other programmabledevice that performs logic operations without processingcomputer-executable instructions. A processor device can also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration. Although described herein primarily with respect todigital technology, a processor device may also include primarily analogcomponents. A computing environment can include any type of computersystem, including, but not limited to, a computer system based on amicroprocessor, a mainframe computer, a digital signal processor, aportable computing device, a device controller, or a computationalengine within an appliance, to name a few.

The elements of a method, process, routine, or algorithm described inconnection with the embodiments disclosed herein can be embodieddirectly in hardware, in a software module executed by a processordevice, or in a combination of the two. A software module can reside inRAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory,registers, hard disk, a removable disk, a CD-ROM, or any other form of anon-transitory computer-readable storage medium. An exemplary storagemedium can be coupled to the processor device such that the processordevice can read information from, and write information to, the storagemedium. In the alternative, the storage medium can be integral to theprocessor device. The processor device and the storage medium can residein an ASIC. The ASIC can reside in a user terminal. In the alternative,the processor device and the storage medium can reside as discretecomponents in a user terminal.

Conditional language used herein, such as, among others, “can,” “may,”“might,” “may,” “e.g.,” and the like, unless specifically statedotherwise, or otherwise understood within the context as used, isgenerally intended to convey that certain embodiments include, whileother embodiments do not include, certain features, elements and/orsteps. Thus, such conditional language is not generally intended toimply that features, elements and/or steps are in any way required forone or more embodiments or that one or more embodiments necessarilyinclude logic for deciding, with or without other input or prompting,whether these features, elements and/or steps are included or are to beperformed in any particular embodiment. The terms “comprising,”“including,” “having,” and the like are synonymous and are usedinclusively, in an open-ended fashion, and do not exclude additionalelements, features, acts, operations, and so forth. Also, the term “or”is used in its inclusive sense (and not in its exclusive sense) so thatwhen used, for example, to connect a list of elements, the term “or”means one, some, or all of the elements in the list.

Disjunctive language such as the phrase “at least one of X, Y, Z,”unless specifically stated otherwise, is otherwise understood with thecontext as used in general to present that an item, term, etc., may beeither X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z).Thus, such disjunctive language is not generally intended to, and shouldnot, imply that certain embodiments require at least one of X, at leastone of Y, or at least one of Z to each be present.

While the phrase “click” may be used with respect to a user selecting acontrol, menu selection, or the like, other user inputs may be used,such as voice commands, text entry, gestures, etc. User inputs may, byway of example, be provided via an interface, such as via text fields,wherein a user enters text, and/or via a menu selection (e.g., a dropdown menu, a list or other arrangement via which the user can check viaa check box or otherwise make a selection or selections, a group ofindividually selectable icons, etc.). When the user provides an input oractivates a control, a corresponding computing system may perform thecorresponding operation. Some or all of the data, inputs andinstructions provided by a user may optionally be stored in a systemdata store (e.g., a database), from which the system may access andretrieve such data, inputs, and instructions. The notifications/alertsand user interfaces described herein may be provided via a Web page, adedicated or non-dedicated phone application, computer application, ashort messaging service message (e.g., SMS, MMS, etc.), instantmessaging, email, push notification, audibly, a pop-up interface, and/orotherwise.

The user terminals described herein may be in the form of a mobilecommunication device (e.g., a cell phone), laptop, tablet computer,interactive television, game console, media streaming device,head-wearable display, networked watch, etc. The user terminals mayoptionally include displays, user input devices (e.g., touchscreen,keyboard, mouse, voice recognition, etc.), network interfaces, etc.

While the above detailed description has shown, described, and pointedout novel features as applied to various embodiments, it can beunderstood that various omissions, substitutions, and changes in theform and details of the devices or algorithms illustrated can be madewithout departing from the spirit of the disclosure. As can berecognized, certain embodiments described herein can be embodied withina form that does not provide all of the features and benefits set forthherein, as some features can be used or practiced separately fromothers. The scope of certain embodiments disclosed herein is indicatedby the appended claims rather than by the foregoing description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope.

What is claimed is:
 1. A system configured to enable a user to obtaininformation related to a medical protocol using an audible query,comprising: a network interface; at least one processing device operableto: generate a profile for a user using user data indicating: how muchinformation the user wants regarding medical treatments associated withthe user, and a degree to which the user is motivated for the user's owncare; access a medical care record associated with the user, the medicalcare record comprising a first medical protocol including patient careinstructions, the patient care instructions including: a first patientcare instruction associated with a first time period, and a secondpatient care instruction associated with a second time period; generatea first personalized interaction model using: the user profile, and theuser medical care record comprising a first medical protocol includingpatient care instructions; update the first personalized interactionmodel at least partly in response to a detection of a new medical carerecord or a modification of the first medical care record; receive overa network using the network interface digitized audio data comprising auser query from a user, the digitized audio data streamed in real timefrom a user device; receive over the network using the network interfacea user identifier associated with the digitized audio data; utilize theuser identifier to access the first personalized interaction modelgenerated using the user profile and the user medical care record; use anatural language processing engine to: translate the digitized audiodata to text; identify, from the translated digitized audio data, a userintent associated with the query, wherein identification of the userintent associated with the query comprises a utilization of mappinginformation to determine what computerized service the query correspondsto; identify, from the translated digitized audio data, a variableassociated with the user intent; access from computer readable memorythe first medical protocol; access, using a computer resource, a currentdate and time; parse the first medical protocol to identify one or morepatient care instructions included in the first medical protocolassociated with a specified date range and/or time period, thatcorresponds to the current date and/or time; utilize: the firstpersonalized interaction model, the first medical protocol, the currentdate and/or time, the identified one or more patient care instructions,the variable associated with the user intent, and the computerizedservice identified using the user intent, to generate a response to theuser query; and cause the response to the user query to be transmittedto and audibly reproduced by the user device.
 2. The system as definedin claim 1, wherein the user device comprises: at least a firstmicrophone; an analog-to-digital converter operatively coupled to thefirst microphone; at least a first speaker transducer; adigital-to-analog converter operatively coupled to the first speakertransducer; a wireless interface; a visual interface; and a digitalmedia processor operatively coupled to the analog-to-digital converter,the digital-to-analog converter, the wireless interface, and the visualinterface.
 3. The system as defined in claim 1, wherein the at least oneprocessor is further operable to: generate the user profile based atleast in part on data provided by the user via an electronic form; usethe generated user profile to generate the first personalizedinteraction model; monitor interactions of the user with the system; usethe monitored interactions of the user with the system to update thefirst personalized interaction model; and interact with the user usingthe updated first personalized interaction model.
 4. The system asdefined in claim 1, wherein the at least one processor is furtheroperable to: detect a change in a status of the user, the change instatus detected using a sensor; and at least partly in response todetecting the change in the status of the user using the sensor, updatethe first personalized interaction model.
 5. The system as defined inclaim 1, wherein the computerized service is hosted by a third partysystem, the at least one processor is further operable to: identify anidentifier associated with the computerized service; pass thecomputerized service identifier to the third party system; pass at leasta portion of the user query in association with the computerized serviceidentifier to the third party system; and receive data generated by thecomputerized service from the third party system, wherein the generatedresponse to the user query comprises the received data generated by thecomputerized service.
 6. The system as defined in claim 1, wherein theat least one processor is further operable to: perform natural languagegeneration to thereby produce natural sounding responses to userqueries, the natural language generation comprising converting data intoa natural language representation using content determination, documentstructuring, aggregation, lexical choice, and/or referring expressiongeneration.
 7. The system as defined in claim 1, wherein the at leastone processor is further operable to: map phrases to intent utilizing aphrase/word co-occurrence matrix and/or a neural network comprising aninput layer, an output layer, and one or more hidden layers.
 8. Thesystem as defined in claim 1, wherein the at least one processor isfurther operable to: identify a failure to map a user phrase to anintent; and log the failure to map the user phrase to an intent.
 9. Thesystem as defined in claim 1, wherein the at least one processor isfurther operable to: access a second medical protocol associated withthe user identifier; determine if the first medical protocol includesone or more instructions that conflict with one or more instructions inthe second protocol; and at least partly in response to determining thatthe first medical protocol includes one or more instructions thatconflict with one or more instructions in the second medical protocol,generate a corresponding personalized communication and cause thepersonalized communication to be transmitted to one or moredestinations.
 10. The system as defined in claim 1, wherein the at leastone processor is further operable to: determine that an additionalcommunication from the user is needed to generate a response to the userquery; based on the determination that an additional communication fromthe user is needed to generate a response to the user query, generate aquery requesting the additional user communication; cause the generatedresponse to be audibly reproduced by the user device; and receive fromthe user device the additional communication from the user, wherein theresponse to the user query is generated using the communication from theuser.
 11. The system as defined in claim 1, wherein the variable isassociated with a medicines prescribed for the user.
 12. The system asdefined in claim 1, wherein the at least one processor is furtheroperable to: analyze a plurality of audio communications from the user;determine a frequency of communications from the user over a first timeperiod; and based at least on the frequency of communications over thefirst time period, determine whether a communication is to betransmitted to a second user.
 13. The system as defined in claim 1,wherein the at least one processor is further operable to: determine ifa first event has occurred; and at least partly in response to adetermination that the first event has occurred, generate an updatedpersonalized interaction model.
 14. The system as defined in claim 1,wherein the first personalized interaction model indicates how the useris to be addressed.
 15. The system as defined in claim 1, wherein thefirst personalized interaction model indicates what type of ancillarycontent is be provided to the user in addition to the response to theuser query.
 16. The system as defined in claim 1, wherein the first oneor more patient care instructions comprise a proscribed activityassociated with a specified time period.
 17. The system as defined inclaim 1, wherein the at least one processor is further operable toauthenticate the user by generating a voiceprint from the digitizedaudio data and comparing the generated voiceprint with a firstvoiceprint stored in memory, and authenticating the user at least partlyin response to determining that the generated voice print corresponds tothe first voiceprint.
 18. The system as defined in claim 1, wherein theat least one processor is further operable to: select image contentbased at least in part on the identified first one or more patient careinstructions; cause the image selected based at least in part on theidentified one or more patient care instructions to be transmitted anddisplayed by the user device.
 19. A computerized method, the methodcomprising: generating a profile for a user using user data indicating:how much medical information the user wants regarding medical issuesassociated with the user; accessing a medical care record associatedwith the user, the medical care record comprising a first medicalprotocol including patient care instructions, the patient careinstructions including: a first patient care instruction associated witha first time period, and a second patient care instruction associatedwith a second time period; generating a first personalized interactionmodel using: the user profile, and the user medical care recordcomprising a first medical protocol including patient care instructions;updating the first personalized interaction model at least partly inresponse to a detection of a new medical care record or a modificationof the first medical care record; receiving over a network using anetwork interface digitized audio data comprising a user communicationfrom a user, the digitized audio data received in real time from a userdevice; receiving over the network using the network interface dataidentifying the user; utilizing the user identifier to access the firstpersonalized interaction model generated using the user profile and theuser medical care record; using a natural language processing engine to:translate the digitized audio data to text; identify a user intentassociated with the user communication; identify a variable associatedwith the user intent; identifying, using the user intent identifiedusing the natural language processing engine, what computerized serviceto invoke; accessing from computer readable memory the first medicalprotocol associated with the user; accessing, using a computer resource,a current date and time; parsing the first protocol to identify one ormore patient care instructions included identified in the first medicalprotocol associated with a specified date range and/or time period, thatcorresponds to the current date and/or time; utilizing: the firstpersonalized interaction model, the first medical protocol, theidentified one or more patient care instructions, the variableassociated with the user intent, and the computerized service identifiedusing the user intent, to generate a response to the user communication;and causing the response to the user communication to be transmitted toand audibly reproduced by the user device.
 20. The method as defined inclaim 19, wherein the user device comprises: at least a firstmicrophone; an analog-to-digital converter operatively coupled to thefirst microphone; at least a first speaker transducer; adigital-to-analog converter operatively coupled to the first speakertransducer; a wireless interface; a visual interface; and a digitalmedia processor operatively coupled to the analog-to-digital converter,the digital-to-analog converter, the wireless interface, and the visualinterface.
 21. The method as defined in claim 19, the method furthercomprising: generating the user profile based at least in part on dataprovided by the user via an electronic form; using the generated userprofile to generate the first personalized interaction model; monitoringinteractions of the user with the first personalized interaction model;using the monitored interactions of the user with the first personalizedinteraction model to update the first personalized interaction model;and interacting with the user using the updated first personalizedinteraction model.
 22. The method as defined in claim 19, the methodfurther comprising: detecting a change in a status of the user, thechange in status detected using a sensor; and at least partly inresponse to detecting the change in the status of the user using thesensor, updating the first personalized interaction model.
 23. Themethod as defined in claim 19, the method further comprising:identifying an identifier associated with the computerized service;passing the computerized service identifier to a third party system;passing at least a portion of the user communication in association withthe computerized service identifier; and receiving data from the thirdparty system generated by the computerized service, wherein thegenerated response to the user communication comprises the received datagenerated by the computerized service.
 24. The method as defined inclaim 19, the method further comprising: performing natural languagegeneration to thereby produce natural sounding responses to userqueries, the natural language generation comprising converting data intoa natural language representation using content determination, documentstructuring, aggregation, lexical choice, and/or referring expressiongeneration.
 25. The method as defined in claim 19, the method furthercomprising: mapping phrases to intent utilizing a phrase/wordco-occurrence matrix and/or a neural network comprising an input layer,an output layer, and one or more hidden layers.
 26. The method asdefined in claim 19, the method further comprising: accessing a secondmedical protocol associated with the user identifier; determining if thefirst medical protocol includes one or more instructions that conflictwith one or more instructions in the second medical protocol; and atleast partly in response to determining that the first medical protocolincludes one or more instructions that conflict with one or moreinstructions in the second medical protocol, generating a correspondingpersonalized communication and causing the personalized communication tobe transmitted to one or more destinations.
 27. The method as defined inclaim 19, the method further comprising: determining that an additionalcommunication from the user is needed to generate a response to the usercommunication; based on the determination that an additionalcommunication from the user is needed to generate a response to the usercommunication, generating a communication requesting the additional usercommunication; causing the generated response to be audibly reproducedby the user device; and receiving from the user device the additionalcommunication from the user, wherein the response to the usercommunication is generated using the communication from the user. 28.The method as defined in claim 19, the method further comprising:analyzing a plurality of audio communications from the user; determininga frequency of communications from the user over a first time period;and based at least on the frequency of communications over the firsttime period, determine whether a communication is to be transmitted to asecond user.
 29. The method as defined in claim 19, wherein the firstpersonalized interaction model indicates how the user is to beaddressed.
 30. The method as defined in claim 19, wherein the firstpersonalized interaction model indicates what type of ancillary contentis be provided to the user in addition to the response to the usercommunication.